The prime minister is to say she wants the UK to lead the world in deciding how artificial intelligence can be deployed in a safe and ethical manner. Theresa May will say at the World Economic Forum in Davos that a new advisory body, previously announced in the Autumn Budget, will co-ordinate efforts with other countries. In addition, she will confirm that the UK will join the Davos forum's own council on artificial intelligence. But others may have stronger claims. Earlier this week, Google picked France as the base for a new research centre dedicated to exploring how AI can be applied to health and the environment.

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.

Joint blind source separation (J-BSS) is an emerging data-driven technique for multi-set data-fusion. In this paper, J-BSS is addressed from a tensorial perspective. We show how, by using second-order multi-set statistics in J-BSS, a specific double coupled canonical polyadic decomposition (DC-CPD) problem can be formulated. We propose an algebraic DC-CPD algorithm based on a coupled rank-1 detection mapping. This algorithm converts a possibly underdetermined DC-CPD to a set of overdetermined CPDs. The latter can be solved algebraically via a generalized eigenvalue decomposition based scheme. Therefore, this algorithm is deterministic and returns the exact solution in the noiseless case. In the noisy case, it can be used to effectively initialize optimization based DC-CPD algorithms. In addition, we obtain the determini- stic and generic uniqueness conditions for DC-CPD, which are shown to be more relaxed than their CPD counterpart. Experiment results are given to illustrate the superiority of DC-CPD over standard CPD based BSS methods and several existing J-BSS methods, with regards to uniqueness and accuracy.

Jan. 12, 2018 - The world is rapidly moving toward Industry 4.0 or the Fourth Industrial Revolution, where artificial intelligence (AI) and machine-learning based systems are not only changing the ways we interact with information and computers but also revolutionizing the manufacturing sector. According to a new AI report from Infosys, in the manufacturing and high tech sector specifically, use of machine learning is higher (79 per cent) as is the institutionalization of enterprise knowledge using AI (66 per cent) and cognitive AI-led processes/tasks (60 per cent). Most companies want to automate manufacturing to increase productivity (66 per cent), minimize manual errors (61 per cent), reduce costs (59 per cent) and refocus people's efforts on non-repetitive tasks that benefit from human intervention (50 per cent). The increasing demand for customized products at reasonable rates is the principal driving force behind the need to use various aspects of AI and machine learning in the manufacturing process. Here is how these disruptive technologies are affecting manufacturing now and in coming years.

SINGAPORE: Thousands of jobs for professionals, managers, executives and technicians (PMET) are being created in the professional services sector, in new roles such as cybersecurity consultants, data engineers and legal tech experts. The sector - which includes architecture and engineering services, accounting and advertising - unveiled its industry transformation map (ITM) on Wednesday (Jan 24), which charts its vision to become a "global market leader in high-value and specialist services". At the heart of the roadmap are initiatives to drive innovation and equip the workforce with skill sets in areas such as data science and artificial intelligence over the next five to 10 years, the Economic Development Board (EDB) said. With the roadmap, the professional services sector is projected to grow at an average rate of 4.6 per cent from 2015 to reach a value-add of S$31 billion by 2020. The aim is also to generate 5,500 jobs every year till 2020.

China's war for technology talent is intensifying. Tens of thousands of people are being hired to shore up cybersecurity, help censor online content, and try to make China No.1 in the application of artificial intelligence (AI), as capital pours into both start-ups and more mature businesses at a time when the government is demanding rapid development. "Companies are well-funded and are in serious competition for talent," said Thomas Liang, a former executive at Chinese search giant Baidu who is now running an AI–focused fund. He said that startups in hot sectors like AI often have to offer 50-100 percent pay raises to attract employees away from established technology firms. China's emergence as a global center for technology, with champions such as Alibaba and Tencent now worth more than a trillion dollars combined, has led to a hiring boom and wage growth that starts to puts salaries for the top talent within striking distance of those offered in Silicon Valley.

Khosla Ventures and Data Collective backed 5 startups each. The number of startups entering the healthcare AI space has increased in recent years, with over 50 companies raising their first equity rounds since January 2015. Deals to healthcare-focused AI startups went up from less than 20 in 2012 to nearly 70 in 2016. Last year also saw two new unicorns emerge in the space: China-based iCarbonX and oncology-focused Flatiron Health. "By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries."

The South Korean government is planning to have 85 robots at the Winter Olympic Games in Pyeongchang next month. In December 2017, a humanoid robot named HUBO, made history by carrying the Olympic torch in the city of Daejeon. It used a tool attached to it's arm to cut off a huge chunk of wall and hand over the torch to it's creator, Professor Oh Jun-Ho. He then handed the torch on to another robot, named FX-2. HUBO, developed a few years ago by the Korean Advanced Institute of Science and Technology, was originally designed for rescue missions and won the DARPA robotics challenge in 2015. The FX-2 on the other hand, is a collaboration between HUBO lab and Rainbow Robotics and was built for the purpose of carrying the Olympic torch.

Artificial intelligence (AI) isn't just the buzzword of the moment--it holds the potential to significantly change the marketing landscape in China and help companies market to the segment of one. Bean: One of our companies, OCheng, is applying AI to WeChat commerce. WeChat service accounts are allowed to send a message to their followers once a week. OCheng can take customer relationship management data, look at the content people are engaging with, their purchase history, etc., and use machine learning to personalize these weekly messages. Instead of sending one message to a million people, you can send a million messages that are unique to each user every week.

– This post was originally published on 26-August-2014 on Linkedin. Basic knowledge and introduction on mobile money and its critical success factors, attributes, key stake holders along with meaning were discussed in Mobile Money Basics (updated on 21-Dec-2014). People interested in the use of mobile phones for their payments, sending money to each other (P2P) or checking balance, often ask what is the difference between e-money, mobile money, mobile banking, mobile payments, mobile commerce etc. Most of the consumers who wants to use and even some who are already using these services are confused. As there are no universally accepted/defined definitions.